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信息化应用2020年4期

​基于矩阵分解的高校学生成绩预测研究
薛梦婷
(广东外语外贸大学,广东 广州 510420)

摘  要:学生成绩预测及告警是协助高等院校职能部门人员管理学生学习情况和监测教师教学质量的有效方法。通过提前预测学生考试分数,对预测成绩偏低的学生加强管理,提前重点关注该类学生的学习情况,可以降低学生考试不及格的风险。文章利用矩阵分解算法提取学生历史分数中的关键特征值,并将其用于学生成绩预测。实验结果表明,使用改进的奇异值分解方法预测学生成绩,具有较强的实用性和较好的效果。


关键词:成绩预测;矩阵分解;奇异值分解;学业预警



中图分类号:G434;TP391         文献标识码:A         文章编号:2096-4706(2020)04-0142-04


Research on College Students’Performance Prediction Based on Matrix Decomposition

XUE Mengting

(Guangdong University of Foreign Studies,Guangzhou 510420,China)

Abstract:The prediction and warning of students’performance is an effective method to assist teachers of the functional departments of colleges to manage students’learning and monitor teachers’teaching quality. By predicting students’examination scores in advance,strengthening the management of students with low predicted scores,and focusing on the learning of such students in advance can reduce them the risk of failing the exam. In this paper,we use the matrix factorization algorithms to extract the key eigenvalues from the student’s historical scores and use them to predict student performance. The experimental results show that the improved SVD method is practical and effective in predicting students’performance.

Keywords:performance prediction;matrix decomposition;singular value decomposition;academic warning


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作者简介:薛梦婷(1992.07-),女,汉族,江苏南京人,助理实验师,硕士研究生,研究方向:数据挖掘、中文情感分析、教育信息化。